1 00:00:02,600 --> 00:00:06,960 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. 2 00:00:08,080 --> 00:00:11,680 Speaker 2: Frank Luntz, famed polster and founder of fil Inc, is 3 00:00:11,800 --> 00:00:14,120 Speaker 2: joining us now. Frank, thanks for being back with us 4 00:00:14,200 --> 00:00:17,280 Speaker 2: on Bloomberg TV and radio. We have been talking about 5 00:00:17,280 --> 00:00:20,599 Speaker 2: this entire cycle how tight margins were likely to be. 6 00:00:20,760 --> 00:00:23,279 Speaker 2: Turns out they're not quite as tight in most of 7 00:00:23,320 --> 00:00:26,560 Speaker 2: these battleground states as they were in twenty twenty. And 8 00:00:26,600 --> 00:00:29,120 Speaker 2: I just wonder your takeaway here when it comes to 9 00:00:29,120 --> 00:00:32,960 Speaker 2: whether or not the polls were adequately reflecting the reality 10 00:00:33,080 --> 00:00:37,040 Speaker 2: in America once again. Doesn't it seem like Poles underestimated 11 00:00:37,040 --> 00:00:39,839 Speaker 2: Donald Trump to a small degree. 12 00:00:40,080 --> 00:00:44,880 Speaker 1: Yes, and that is about turnout that every Trump supporter 13 00:00:45,040 --> 00:00:47,800 Speaker 1: became a Trump voter. That is not the case with 14 00:00:48,080 --> 00:00:50,760 Speaker 1: Kamala Harris, and that's one of the reasons why she 15 00:00:50,880 --> 00:00:54,279 Speaker 1: fell short. Certainly, the idea that Trump would get a 16 00:00:54,320 --> 00:00:57,120 Speaker 1: majority of the popular vote is a surprise to a 17 00:00:57,120 --> 00:01:00,520 Speaker 1: lot of people right now. And is the the Iowa 18 00:01:00,600 --> 00:01:03,160 Speaker 1: poll which I want to draw attention to because that 19 00:01:03,360 --> 00:01:06,119 Speaker 1: changed the actual narrative of the campaign. 20 00:01:05,760 --> 00:01:07,080 Speaker 3: For the last forty eight hours. 21 00:01:08,400 --> 00:01:12,559 Speaker 1: Trump ended up winning Iowa by about a dozen points 22 00:01:12,640 --> 00:01:12,880 Speaker 1: or so. 23 00:01:13,360 --> 00:01:15,600 Speaker 3: That the poll had Harris up by three. 24 00:01:16,120 --> 00:01:18,320 Speaker 1: It was not only beyond the margin of err, it 25 00:01:18,400 --> 00:01:22,600 Speaker 1: actually changed how the race was being covered, which is 26 00:01:22,800 --> 00:01:26,520 Speaker 1: really one of the rare times when survey research actually 27 00:01:26,520 --> 00:01:29,160 Speaker 1: becomes part of the narrative. I think that there's a 28 00:01:29,240 --> 00:01:32,080 Speaker 1: lesson for Americans in the future which has spent a 29 00:01:32,160 --> 00:01:34,959 Speaker 1: lot less time talking about who's winning and losing, and 30 00:01:35,040 --> 00:01:38,160 Speaker 1: a lot more time talking about what the candidates say 31 00:01:38,160 --> 00:01:40,800 Speaker 1: they're going to do and why either we should believe 32 00:01:40,840 --> 00:01:42,080 Speaker 1: them or distrust them. 33 00:01:42,319 --> 00:01:44,920 Speaker 4: Sounds like people were wrong about a lot, frank They 34 00:01:44,920 --> 00:01:48,200 Speaker 4: were wrong about the protesters showing up at the DNC, 35 00:01:48,520 --> 00:01:52,360 Speaker 4: they were wrong about violence around polls, wrong about pole watchers, 36 00:01:52,400 --> 00:01:55,639 Speaker 4: wrong about, in some cases even though our polls were tied, 37 00:01:56,080 --> 00:01:59,920 Speaker 4: the idea that there was momentum behind Kamala Harris as well. 38 00:02:00,480 --> 00:02:03,120 Speaker 3: I'm wondering if there's a reckoning here for posters. 39 00:02:03,440 --> 00:02:05,160 Speaker 4: Was there an overcorrection in the sample? 40 00:02:05,160 --> 00:02:06,600 Speaker 3: And what's going through your mind today? 41 00:02:07,120 --> 00:02:09,200 Speaker 1: Well, what's going through my mind, because I've been asked 42 00:02:09,200 --> 00:02:10,840 Speaker 1: this in almost every show, is. 43 00:02:11,720 --> 00:02:12,519 Speaker 3: This is the media. 44 00:02:14,280 --> 00:02:17,399 Speaker 1: The posters did get it wrong, but the media went 45 00:02:17,560 --> 00:02:21,720 Speaker 1: all over this IOWA survey when all over trying to 46 00:02:21,760 --> 00:02:24,840 Speaker 1: see some trends, some movement in one direction or another, 47 00:02:25,400 --> 00:02:28,800 Speaker 1: and that they're the ones who drove this. I tend 48 00:02:28,800 --> 00:02:30,960 Speaker 1: not to talk about polling when I do shows like this, 49 00:02:31,080 --> 00:02:34,800 Speaker 1: I talk about policy. I talk about language, what the 50 00:02:34,840 --> 00:02:39,240 Speaker 1: public wants to see and hear, and whether the politicians 51 00:02:39,280 --> 00:02:42,040 Speaker 1: are doing it or not. And so much of this 52 00:02:42,800 --> 00:02:45,840 Speaker 1: is actually driven by those who ask the questions rather 53 00:02:45,880 --> 00:02:48,880 Speaker 1: than people like me who answer them, because we wouldn't 54 00:02:48,919 --> 00:02:51,359 Speaker 1: answer them if we weren't asking them. I don't want 55 00:02:51,400 --> 00:02:53,560 Speaker 1: to make a blanket statement because I take this so 56 00:02:53,760 --> 00:02:57,640 Speaker 1: seriously and I so approve of the way your show 57 00:02:57,919 --> 00:03:03,320 Speaker 1: handles politics the best shows in all of television or politics. 58 00:03:03,840 --> 00:03:05,440 Speaker 3: But I do think that there needs to be a 59 00:03:05,480 --> 00:03:07,000 Speaker 3: reckoning for. 60 00:03:08,919 --> 00:03:13,079 Speaker 1: What we choose to focus on and how we cover it, 61 00:03:13,160 --> 00:03:17,080 Speaker 1: because in the end it becomes misleading or even detrimental 62 00:03:17,120 --> 00:03:21,799 Speaker 1: to the political process, as that Iowas survey clearly was well. 63 00:03:21,840 --> 00:03:24,519 Speaker 2: Frank, we appreciate the kind words, and of course, there 64 00:03:24,560 --> 00:03:27,720 Speaker 2: always is room for critique when we consider how the 65 00:03:27,800 --> 00:03:30,640 Speaker 2: narrative is shaped in America, and media plays a role 66 00:03:30,919 --> 00:03:32,880 Speaker 2: in that as well. I think we can all agree. 67 00:03:33,040 --> 00:03:36,160 Speaker 2: Earlier on in this cycle, there was a few conversations 68 00:03:36,160 --> 00:03:38,720 Speaker 2: that happened in quick succession, one being whether or not 69 00:03:38,760 --> 00:03:42,200 Speaker 2: the media was putting too much focus on the age 70 00:03:42,200 --> 00:03:44,600 Speaker 2: issue for Joe Biden. Then became whether or not the 71 00:03:44,640 --> 00:03:48,360 Speaker 2: media was complicit in covering up how deep those issues 72 00:03:48,400 --> 00:03:50,960 Speaker 2: may have run for the current president. And I just wonder, 73 00:03:51,000 --> 00:03:53,160 Speaker 2: as we consider the role of Joe Biden and all 74 00:03:53,200 --> 00:03:56,960 Speaker 2: of this, his late withdrawal from his reelection campaign, if 75 00:03:57,040 --> 00:03:59,960 Speaker 2: ultimately you think that made a difference, if the timing mattered, 76 00:04:00,080 --> 00:04:01,840 Speaker 2: or if it was never going to be possible for 77 00:04:01,880 --> 00:04:06,240 Speaker 2: an incumbent administration given the kind of inflation experienced during it, 78 00:04:06,480 --> 00:04:09,560 Speaker 2: to keep hold of the White House, don't I don't 79 00:04:09,600 --> 00:04:10,040 Speaker 2: believe that. 80 00:04:10,760 --> 00:04:13,440 Speaker 1: I challenged the narrative which has been put forward now 81 00:04:14,200 --> 00:04:18,799 Speaker 1: for weeks. Vice President Harris had one of the sharpest 82 00:04:19,000 --> 00:04:23,680 Speaker 1: fastest rises of any candidate modern history. She went from 83 00:04:23,760 --> 00:04:26,640 Speaker 1: five points down when she got into the race to 84 00:04:26,720 --> 00:04:28,880 Speaker 1: three and a half points up in a matter of 85 00:04:28,960 --> 00:04:32,600 Speaker 1: a few weeks. Because she was joyful. She talked about 86 00:04:32,600 --> 00:04:35,040 Speaker 1: the things she wanted to do, instead of the negativity 87 00:04:35,560 --> 00:04:38,800 Speaker 1: which he decried again and again. She was hopeful and 88 00:04:38,839 --> 00:04:41,679 Speaker 1: optimistic and talked about all the things that she wanted 89 00:04:41,680 --> 00:04:45,400 Speaker 1: to get done. But then after the convention, she turned dark, 90 00:04:46,040 --> 00:04:48,679 Speaker 1: she turned negative. It sounded as much like a Trump 91 00:04:48,720 --> 00:04:50,560 Speaker 1: campaign as it did a Harris campaign. 92 00:04:51,120 --> 00:04:52,560 Speaker 3: And that was when she hit her ceiling. 93 00:04:53,440 --> 00:04:56,960 Speaker 1: And then she and by changing this by being joyful 94 00:04:57,080 --> 00:05:04,360 Speaker 1: and then being harshly negative, calling Trump a fascist, voters 95 00:05:04,360 --> 00:05:06,000 Speaker 1: started to wonder who is she? 96 00:05:06,720 --> 00:05:09,080 Speaker 3: Is she authentic? Is she genuine? 97 00:05:09,600 --> 00:05:12,920 Speaker 1: How do you go from being joyful to damning your opponents? 98 00:05:13,640 --> 00:05:16,159 Speaker 1: And then Biden, of course made the comment about Trump's voters, 99 00:05:17,000 --> 00:05:19,160 Speaker 1: and it just it didn't ring true. 100 00:05:19,279 --> 00:05:23,360 Speaker 3: That's number one and number two. She never articulated. 101 00:05:22,720 --> 00:05:25,360 Speaker 1: Exactly what she wanted to do in the first hour, 102 00:05:25,760 --> 00:05:29,560 Speaker 1: in the first day, first week, first month, first one, 103 00:05:29,640 --> 00:05:32,200 Speaker 1: under days and so on. If she had done that 104 00:05:32,240 --> 00:05:35,480 Speaker 1: in the CNN town hall where it's done live, if 105 00:05:35,480 --> 00:05:37,560 Speaker 1: she'd done that in the sixty minutes interview or the 106 00:05:37,600 --> 00:05:40,680 Speaker 1: Fox interview, any of these, if she had done that 107 00:05:40,760 --> 00:05:43,719 Speaker 1: until voters exactly what she wanted to do, she would 108 00:05:43,760 --> 00:05:45,960 Speaker 1: have done much better because then she would have been 109 00:05:46,000 --> 00:05:49,880 Speaker 1: about policy, and that's where she was weakest. But instead 110 00:05:50,520 --> 00:05:55,160 Speaker 1: she got driven around. She never answered the questions that 111 00:05:55,240 --> 00:05:58,520 Speaker 1: voters had and so she never crossed that threshold. Whereas 112 00:05:58,560 --> 00:06:01,120 Speaker 1: Donald Trump we knew him. There's nothing more we can 113 00:06:01,200 --> 00:06:04,080 Speaker 1: learn about him. We knew his weaknesses, we knew his strengths, 114 00:06:04,240 --> 00:06:06,560 Speaker 1: we knew his record because we saw for four years. 115 00:06:06,960 --> 00:06:08,880 Speaker 3: So her criticizing. 116 00:06:08,240 --> 00:06:11,880 Speaker 1: Him didn't add anything to her, did not detract from him, 117 00:06:12,160 --> 00:06:13,919 Speaker 1: and I think that that's one of the reasons why. 118 00:06:13,760 --> 00:06:17,280 Speaker 4: She are the diagnosis from Frank LUNs on Bloomberg TV 119 00:06:17,400 --> 00:06:20,520 Speaker 4: and Radio. All of that said, Frank, what did we 120 00:06:20,600 --> 00:06:23,520 Speaker 4: learn about our nation last night, particularly if this in 121 00:06:23,600 --> 00:06:26,000 Speaker 4: fact was about men versus women? 122 00:06:27,960 --> 00:06:30,159 Speaker 1: I love that question, and that's a question that we 123 00:06:30,200 --> 00:06:33,080 Speaker 1: need to be talking about over the coming weeks and months, 124 00:06:33,400 --> 00:06:35,400 Speaker 1: because there are some things that are more important than 125 00:06:35,400 --> 00:06:35,880 Speaker 1: an election. 126 00:06:36,360 --> 00:06:38,520 Speaker 3: It's the next generation. And what are they learning. 127 00:06:39,279 --> 00:06:42,320 Speaker 1: They're learning that it's okay to tell your opponent apart. 128 00:06:42,520 --> 00:06:43,680 Speaker 3: They're learning that there. 129 00:06:43,640 --> 00:06:47,800 Speaker 1: Is no bounds to negativity, that there are right and 130 00:06:47,880 --> 00:06:50,200 Speaker 1: wrong ways, but they need to learn that they're right 131 00:06:50,240 --> 00:06:54,200 Speaker 1: and wrong ways to approach politics, to approach economics, to 132 00:06:54,240 --> 00:06:57,280 Speaker 1: approach day to day life. And I'm just afraid that 133 00:06:57,360 --> 00:06:59,920 Speaker 1: what we now learned is the wrong thing, which is 134 00:07:00,040 --> 00:07:03,919 Speaker 1: as anything goes at any time for any reason, and 135 00:07:03,960 --> 00:07:05,359 Speaker 1: that fightens me for the future. 136 00:07:06,360 --> 00:07:09,000 Speaker 2: Well, Okay, So if we keep looking at demographics here 137 00:07:09,000 --> 00:07:11,320 Speaker 2: and what the future may hold, Frank, I look at 138 00:07:11,360 --> 00:07:14,920 Speaker 2: Donald Trump's victory in Miami Dade last night. We haven't 139 00:07:14,920 --> 00:07:18,040 Speaker 2: seen a Republican win that county for decades. It obviously 140 00:07:18,120 --> 00:07:21,240 Speaker 2: is majority Hispanic. We did see a sizable break among 141 00:07:21,360 --> 00:07:24,120 Speaker 2: Latinos for Donald Trump in a way we haven't seen 142 00:07:24,160 --> 00:07:26,920 Speaker 2: in the past. Obviously, movement for black voters as well. 143 00:07:26,960 --> 00:07:29,360 Speaker 2: And I wonder if you think those demographic shifts are 144 00:07:29,480 --> 00:07:32,400 Speaker 2: unique to this candidate who is now president elect, or 145 00:07:32,440 --> 00:07:34,440 Speaker 2: if that may be something more permanent. 146 00:07:35,400 --> 00:07:38,480 Speaker 1: It's unique to this candidate, but also to this time 147 00:07:39,320 --> 00:07:41,840 Speaker 1: that it doesn't matter with your white, black, brown, It 148 00:07:41,880 --> 00:07:45,000 Speaker 1: doesn't matter if you have trouble at fording food, put 149 00:07:45,000 --> 00:07:47,920 Speaker 1: food on your tables, put gas in your car, or 150 00:07:48,120 --> 00:07:50,320 Speaker 1: the healthcare you need and the housing that you want, 151 00:07:50,840 --> 00:07:52,680 Speaker 1: And it doesn't matter what your ethnicity is. 152 00:07:53,040 --> 00:07:54,000 Speaker 3: What matters is you're. 153 00:07:53,920 --> 00:07:57,880 Speaker 1: Struggling, you're living paycheck to paycheck, and that's what's happening 154 00:07:57,960 --> 00:08:02,200 Speaker 1: right now. And Donald Trump an empathy to that much 155 00:08:02,480 --> 00:08:05,400 Speaker 1: more explicitly than Harris did. 156 00:08:05,880 --> 00:08:08,240 Speaker 3: She tried to run away from it. Now. 157 00:08:08,280 --> 00:08:11,560 Speaker 1: Trump's greatest weakness is he didn't focus enough on prices, 158 00:08:11,840 --> 00:08:16,040 Speaker 1: on costs, on affordability that instead he got sidetracked by 159 00:08:16,160 --> 00:08:17,760 Speaker 1: issues that did not matter. 160 00:08:18,320 --> 00:08:20,080 Speaker 3: And in fact, I want to acknowledge something. 161 00:08:20,120 --> 00:08:23,400 Speaker 1: I'm going to go back to that presidential debate that 162 00:08:23,520 --> 00:08:27,480 Speaker 1: clearly she did relatively well and he did relatively poorly. 163 00:08:28,000 --> 00:08:30,640 Speaker 3: In the end, it did not matter. I thought the 164 00:08:30,720 --> 00:08:32,280 Speaker 3: debate performance would cost. 165 00:08:32,080 --> 00:08:36,440 Speaker 1: Him his candidacy, and instead it actually did not matter. 166 00:08:36,480 --> 00:08:39,959 Speaker 1: And that's another learning that America has to face that 167 00:08:40,080 --> 00:08:42,920 Speaker 1: even when you put two candidates side by side, the 168 00:08:43,000 --> 00:08:46,520 Speaker 1: outcome does not necessarily matter and who wins for president. 169 00:08:47,280 --> 00:08:49,920 Speaker 4: Really great to have you back, Frank Frank Luntz, founder 170 00:08:50,000 --> 00:08:52,760 Speaker 4: CEO FI L and just the voice we were looking 171 00:08:52,760 --> 00:08:54,480 Speaker 4: to hear today. Thanks for being with us throughout this 172 00:08:54,679 --> 00:08:55,520 Speaker 4: entire campaign.